A novel selection method of CMIP6 GCMs for robust climate projection

The selection of global climate models (GCMs) is a major challenge for reliable projection of climate. A novel method is introduced in this study to select couple model intercomparison project phase 6 (CMIP6) GCMs. Climatology maps of GCM simulated precipitation, maximum temperature and minimum temp...

Full description

Saved in:
Bibliographic Details
Main Authors: Hamed, Mohammed Magdy, Nashwan, Mohamed Salem, Shahid, Shamsuddin
Format: Article
Published: John Wiley and Sons Ltd 2022
Subjects:
Online Access:http://eprints.utm.my/id/eprint/101021/
http://dx.doi.org/10.1002/joc.7461
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
id my.utm.101021
record_format eprints
spelling my.utm.1010212023-05-23T10:40:18Z http://eprints.utm.my/id/eprint/101021/ A novel selection method of CMIP6 GCMs for robust climate projection Hamed, Mohammed Magdy Nashwan, Mohamed Salem Shahid, Shamsuddin TA Engineering (General). Civil engineering (General) The selection of global climate models (GCMs) is a major challenge for reliable projection of climate. A novel method is introduced in this study to select couple model intercomparison project phase 6 (CMIP6) GCMs. Climatology maps of GCM simulated precipitation, maximum temperature and minimum temperature data were rasterized to form 8-bit grey scale images, which were subsequently merged to form a colour image. The GCMs' climatology images were compared with the climatology image prepared using gridded climate data for their performance assessment. This allowed an unbiased comparison of GCMs according to their ability to reconstruct three major climate variables' climatology. The proposed method was employed for CMIP6 GCMs selections and projection of climate of Egypt for different shared socioeconomic pathway (SSP) scenarios. The study recognized four GCMs suitable for climate projections of Egypt, ACCESS-CM2, AWI-CM-1-1-MR, BCC-CSM2-MR and MRI-ESM2-0. The selected models' biases in simulating precipitation and temperature showed consistent results, underestimating the north and overestimating in the south for rainfall. However, the projections of different GCMs showed a considerable inconsistency. Overall, the results indicated a possible decrease in annual and winter precipitation in the range of 0 to −50% in the high rainfall regions in the north and a large increase in the low rainfall (~5 mm) region in the south. The low rainfall zone in the south showed a gradual expansion with the increase of SSPs and time. The maximum and minimum temperature showed a higher increase in the south, particularly southeast (>6°C in the far future) and least in the northern coastal zone. John Wiley and Sons Ltd 2022 Article PeerReviewed Hamed, Mohammed Magdy and Nashwan, Mohamed Salem and Shahid, Shamsuddin (2022) A novel selection method of CMIP6 GCMs for robust climate projection. International Journal of Climatology, 42 (8). pp. 4258-4272. ISSN 0899-8418 http://dx.doi.org/10.1002/joc.7461 DOI: 10.1002/joc.7461
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Hamed, Mohammed Magdy
Nashwan, Mohamed Salem
Shahid, Shamsuddin
A novel selection method of CMIP6 GCMs for robust climate projection
description The selection of global climate models (GCMs) is a major challenge for reliable projection of climate. A novel method is introduced in this study to select couple model intercomparison project phase 6 (CMIP6) GCMs. Climatology maps of GCM simulated precipitation, maximum temperature and minimum temperature data were rasterized to form 8-bit grey scale images, which were subsequently merged to form a colour image. The GCMs' climatology images were compared with the climatology image prepared using gridded climate data for their performance assessment. This allowed an unbiased comparison of GCMs according to their ability to reconstruct three major climate variables' climatology. The proposed method was employed for CMIP6 GCMs selections and projection of climate of Egypt for different shared socioeconomic pathway (SSP) scenarios. The study recognized four GCMs suitable for climate projections of Egypt, ACCESS-CM2, AWI-CM-1-1-MR, BCC-CSM2-MR and MRI-ESM2-0. The selected models' biases in simulating precipitation and temperature showed consistent results, underestimating the north and overestimating in the south for rainfall. However, the projections of different GCMs showed a considerable inconsistency. Overall, the results indicated a possible decrease in annual and winter precipitation in the range of 0 to −50% in the high rainfall regions in the north and a large increase in the low rainfall (~5 mm) region in the south. The low rainfall zone in the south showed a gradual expansion with the increase of SSPs and time. The maximum and minimum temperature showed a higher increase in the south, particularly southeast (>6°C in the far future) and least in the northern coastal zone.
format Article
author Hamed, Mohammed Magdy
Nashwan, Mohamed Salem
Shahid, Shamsuddin
author_facet Hamed, Mohammed Magdy
Nashwan, Mohamed Salem
Shahid, Shamsuddin
author_sort Hamed, Mohammed Magdy
title A novel selection method of CMIP6 GCMs for robust climate projection
title_short A novel selection method of CMIP6 GCMs for robust climate projection
title_full A novel selection method of CMIP6 GCMs for robust climate projection
title_fullStr A novel selection method of CMIP6 GCMs for robust climate projection
title_full_unstemmed A novel selection method of CMIP6 GCMs for robust climate projection
title_sort novel selection method of cmip6 gcms for robust climate projection
publisher John Wiley and Sons Ltd
publishDate 2022
url http://eprints.utm.my/id/eprint/101021/
http://dx.doi.org/10.1002/joc.7461
_version_ 1768006597662998528